Recent explainable AI research has focused on class activation maps
[1]}[2]}[3]} [4]}[5]}[6]}[7]}, which visualize salient regions used for classification.
For facial recognition, prior work has shown this is almost always the eyes, nose, and upper lip of the face [8]}. In facial identification, a probe image is given to a face matching system, which returns the top \(K\)  identities from a gallery.
A natural question is why the matching system picked the top match instead of the second top match (or remaining top K matches).
One way to give an answer to this question is to highlight the region(s) that match a given identity more than the second identity or other identities.
This saliency map should be larger for the regions that contribute the most to the identity and not others.
In this paper, our goal is to highlight the regions that are responsible for matching a given image to one identity versus a similar identity.
